About Sumedh Khodke

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    Anywhere in the United States
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About me

I’m a second-year graduate student in Data Science at SUNY University at Buffalo, graduating in December 2022. I previously worked as an ML SWE at a growth stage startup with a total experience of 2.5yrs.

My current research interests lie in Applied Machine Learning, Language modelling and ML training optimization techniques. I like to work in the sphere of intersection of Machine Learning and Software engineering stuff with special interests in Natural Language Processing. Always on the lookout to explore and contribute in the space intersecting these fields.

For a detailed overview of my work and projects, please see https://sumedhkhodke.com/

• Languages: Expert – Python, Intermediate – C++, Basic – Java/J2EE, C, Golang, Jax, R
• Libraries: Pandas, NumPy, SciPy, Sk-learn, Keras, PyTorch, TensorFlow, Flair, Fastai 2, NLTK, Spacy
• Data Visualization: Tableau, PowerBI, d3.js, seaborn, matplotlib
• Tools and Databases: Celery, Git, SVN, Bitbucket, Docker, Spark, Arrow, SQL, Redis, MongoDB
• Web Development and Cloud: HTML5, CSS3, Django, Flask, FastAPI, Streamlit, AWS, GCP
• Certifications: Coursera – Deep Learning Specialization, AI for Everyone, AI for Medical Diagnosis

Education

  • 2023
    University at Buffalo, The State University of New York

    MS, Data Science

    Coursework: Probability, Statistical Learning, Numerical Computing, Analysis of Algorithms, Machine Learning, Deep Learning

  • 2018
    Pune Institute of Computer Technology, University of Pune

    Bachelor of Engineering, Computer Engineering

    Coursework: Data Structures, Operating Systems, Business Intelligence, Databases, Advanced Mathematics, Software Engineering

Experience

  • 2019 - 2021
    Rubiscape - Inteliment Technologies

    Software Engineer, Machine Learning

    • Designed and developed an NLP project on text classification with comparative performance analysis for word embeddings using Flair stacked-embedding framework, using CNN-LSTM, and using Transformer based Attention mechanism achieving a maximum of 73% F-1 score
    • Worked as Module Lead and developer for Rubisight, an interactive data visualization software. Responsible to handle elements to define, conceptualize, design, develop and optimize it
    • Worked as a member of technical staff at Rubiscape, a data science platform. Responsible for implementing several customized data aggregators and machine learning implementations at a production scale as platform features

  • 2017 - 2018
    Walnut App Division

    Machine Learning Intern, Research

    • Researched and benchmarked NLP tasks of Word Embeddings, Text classification, Sentiment Analysis and NER followed by rapid prototyping

Honors & awards

Skills